Electroencephalography (EEG) Signal Processing: Advanced Technology and Application
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".
Deadline for manuscript submissions: 20 December 2025 | Viewed by 120
Special Issue Editors
Interests: HD-EEG; sleep physiology; neuroplasticity; TMS-EEG
Interests: HD-EEG; signal processing; microstate analysis; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
We invite you to submit your research work to our Special Issue, entitled “Electroencephalography (EEG) Signal Processing: Advanced Technology and Application”.
While conventional EEG remains a cornerstone, by leveraging recent advancements in EEG signal processing and analysis, we can now extract more meaningful information from complex EEG data, which has deepened our understanding of brain dynamics in health and disease, as well as strengthening diagnostic capacities and novel rehabilitative interventions.
This Special Issue aims to bring together and present significant advances in EEG signal processing and analysis. In this Special Issue, original research articles and reviews are welcome. Specifically, submissions should focus on novel developments in the analysis techniques of periodic and aperiodic EEG signals, new advancements in EEG source reconstruction algorithms, and emerging insights from EEG connectivity analyses. We also welcome contributions detailing innovations in applying machine learning to EEG data, progress in neurofeedback and brain–computer interfaces (BCIs), and data processing challenges of wearable and ambulatory EEG systems. Furthermore, we strongly encourage submissions that address the progress in algorithmic and computational tools for integrating EEG with other neuroimaging (fMRI, MEG, and fNIRS) and neurophysiological techniques (TMS and EMG).
We look forward to receiving your contributions.
Dr. Angelica Quercia
Dr. Pierpaolo Croce
Guest Editors
Manuscript Submission Information
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Keywords
- electroencephalography signal processing
- EEG complexity
- microstate analysis
- source reconstruction
- connectivity analysis
- machine learning
- neurofeedback
- brain–computer interfaces (BCIs)
- wearable EEG
- multimodal neurophysiology
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